code: def test_calibrate_denoiser_extra_output():
      parameter_ranges = {"sigma": np.linspace(0.1, 1, 5) / 2}
      _, (parameters_tested, losses) = calibrate_denoiser(
          noisy_img,
          _denoise_wavelet,
          denoise_parameters=parameter_ranges,
          extra_output=True,
      )
  
      all_denoised = [
          denoise_invariant(
              noisy_img,
              _denoise_wavelet,
              denoiser_kwargs=denoiser_kwargs,
          )
          for denoiser_kwargs in parameters_tested
      ]
  
      ground_truth_losses = [mse(img, test_img) for img in all_denoised]
      assert_(np.argmin(losses) == np.argmin(ground_truth_losses))
  
file_path: scikit-image/skimage/restoration/tests/test_j_invariant.py
imports: import functools
  import numpy
  import pytest
  from skimage._shared.testing import assert_
  from skimage._shared.utils import _supported_float_type
  from skimage.data import binary_blobs
  from skimage.data import camera, chelsea
  from skimage.metrics import mean_squared_error
  from skimage.restoration import calibrate_denoiser, denoise_wavelet
  from skimage.restoration.j_invariant import denoise_invariant
  from skimage.util import img_as_float, random_noise
  from skimage.restoration.tests.test_denoise import xfail_without_pywt
label_desc: Use image node_id 4 for calling a global function with example usage: test_calibrate_denoiser_extra_output() without return types